Github user marmbrus commented on a diff in the pull request:
https://github.com/apache/spark/pull/15102#discussion_r80562234
--- Diff:
external/kafka-0-10-sql/src/main/scala/org/apache/spark/sql/kafka010/KafkaSource.scala
---
@@ -0,0 +1,344 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.kafka010
+
+import java.{util => ju}
+
+import scala.collection.JavaConverters._
+
+import org.apache.kafka.clients.consumer.{Consumer, KafkaConsumer}
+import
org.apache.kafka.clients.consumer.internals.NoOpConsumerRebalanceListener
+import org.apache.kafka.common.TopicPartition
+
+import org.apache.spark.SparkContext
+import org.apache.spark.internal.Logging
+import org.apache.spark.scheduler.ExecutorCacheTaskLocation
+import org.apache.spark.sql._
+import org.apache.spark.sql.execution.streaming._
+import org.apache.spark.sql.kafka010.KafkaSource._
+import org.apache.spark.sql.types._
+
+/**
+ * A [[Source]] that uses Kafka's own [[KafkaConsumer]] API to reads data
from Kafka. The design
+ * for this source is as follows.
+ *
+ * - The [[KafkaSourceOffset]] is the custom [[Offset]] defined for this
source that contains
+ * a map of TopicPartition -> offset. Note that this offset is 1 +
(available offset). For
+ * example if the last record in a Kafka topic "t", partition 2 is
offset 5, then
+ * KafkaSourceOffset will contain TopicPartition("t", 2) -> 6. This is
done keep it consistent
+ * with the semantics of `KafkaConsumer.position()`.
+ *
+ * - The [[ConsumerStrategy]] class defines which Kafka topics and
partitions should be read
+ * by this source. These strategies directly correspond to the different
consumption options
+ * in . This class is designed to return a configured
+ * [[KafkaConsumer]] that is used by the [[KafkaSource]] to query for
the offsets.
+ * See the docs on
[[org.apache.spark.sql.kafka010.KafkaSource.ConsumerStrategy]] for
+ * more details.
+ *
+ * - The [[KafkaSource]] written to do the following.
+ *
+ * - As soon as the source is created, the pre-configured KafkaConsumer
returned by the
+ * [[ConsumerStrategy]] is used to query the initial offsets that this
source should
+ * start reading from. This used to create the first batch.
+ *
+ * - `getOffset()` uses the KafkaConsumer to query the latest available
offsets, which are
+ * returned as a [[KafkaSourceOffset]].
+ *
+ * - `getBatch()` returns a DF that reads from the 'start offset' until
the 'end offset' in
+ * for each partition. The end offset is excluded to be consistent
with the semantics of
+ * [[KafkaSourceOffset]] and `KafkaConsumer.position()`.
+ *
+ * - The DF returned is based on [[KafkaSourceRDD]] which is constructed
such that the
+ * data from Kafka topic + partition is consistently read by the same
executors across
+ * batches, and cached KafkaConsumers in the executors can be reused
efficiently. See the
+ * docs on [[KafkaSourceRDD]] for more details.
+ */
+private[kafka010] case class KafkaSource(
+ sqlContext: SQLContext,
+ consumerStrategy: ConsumerStrategy,
+ executorKafkaParams: ju.Map[String, Object],
+ sourceOptions: Map[String, String])
+ extends Source with Logging {
+
+ private val consumer = consumerStrategy.createConsumer()
+ private val sc = sqlContext.sparkContext
+ private val initialPartitionOffsets = fetchPartitionOffsets(seekToLatest
= false)
+ logInfo(s"Initial offsets: $initialPartitionOffsets")
+
+ override def schema: StructType = KafkaSource.kafkaSchema
+
+ /** Returns the maximum available offset for this source. */
+ override def getOffset: Option[Offset] = {
+ val offset = KafkaSourceOffset(fetchPartitionOffsets(seekToLatest =
true))
+ logInfo(s"GetOffset: $offset")
+ Some(offset)
+ }
+
+ /** Returns the data that is between the offsets [`start`, `end`), i.e.
end is exclusive. */
+ override def getBatch(start: Option[Offset], end: Offset): DataFrame = {
+ logInfo(s"GetBatch called with start = $start, end = $end")
+ val untilPartitionOffsets = KafkaSourceOffset.getPartitionOffsets(end)
+ val fromPartitionOffsets = start match {
+ case Some(prevBatchEndOffset) =>
+ KafkaSourceOffset.getPartitionOffsets(prevBatchEndOffset)
+ case None =>
+ initialPartitionOffsets
+ }
+
+ // Find the new partitions, and get their earliest offsets
+ val newPartitions =
untilPartitionOffsets.keySet.diff(fromPartitionOffsets.keySet)
+ val newPartitionOffsets = if (newPartitions.nonEmpty) {
+ fetchNewPartitionEarliestOffsets(newPartitions.toSeq)
+ } else {
+ Map.empty[TopicPartition, Long]
+ }
+ logInfo(s"Partitions added: $newPartitionOffsets")
+ newPartitionOffsets.filter(_._2 != 0).foreach { case (p, o) =>
+ logWarning(s"Added partition $p starts from $o instead of 0, some
data may have been missed")
+ }
+
+ val deletedPartitions =
fromPartitionOffsets.keySet.diff(untilPartitionOffsets.keySet)
+ logWarning(s"Partitions removed: $deletedPartitions, some data may
have been missed")
+
+ // Sort the partitions and current list of executors to consistently
assign each partition
+ // to the executor. This allows cached KafkaConsumers in the executors
to be re-used to
+ // read the same partition in every batch.
+ val topicPartitionOrdering = new Ordering[TopicPartition] {
+ override def compare(l: TopicPartition, r: TopicPartition): Int = {
+ implicitly[Ordering[(String, Long)]].compare(
+ (l.topic, l.partition),
+ (r.topic, r.partition))
+ }
+ }
+
+ // Use the until partitions to calculate offset ranges to ignore
partitions that have
+ // been deleted
+ val sortedTopicPartitions =
untilPartitionOffsets.keySet.toSeq.sorted(topicPartitionOrdering)
+ logDebug("Sorted topicPartitions: " +
sortedTopicPartitions.mkString(", "))
+
+ val sortedExecutors = getSortedExecutorList(sc)
+ val numExecutors = sortedExecutors.length
+ logDebug("Sorted executors: " + sortedExecutors.mkString(", "))
+
+ // Calculate offset ranges
+ val offsetRanges = sortedTopicPartitions.map { tp =>
+ val fromOffset = fromPartitionOffsets.get(tp).getOrElse {
+ newPartitionOffsets.getOrElse(tp, {
+ // This should not happen since newPartitionOffsets contains all
partitions not in
+ // fromPartitionOffsets
+ throw new IllegalStateException(s"$tp doesn't have a from
offset")
+ })
+ }
+ val untilOffset = untilPartitionOffsets(tp)
+ val preferredLoc = if (numExecutors > 0) {
+ Some(sortedExecutors(positiveMod(tp.hashCode, numExecutors)))
+ } else None
+ KafkaSourceRDDOffsetRange(tp, fromOffset, untilOffset, preferredLoc)
+ }.toArray
+
+ // Create a RDD that reads from Kafka and get the (key, value) pair as
byte arrays.
+ val rdd = new KafkaSourceRDD(
+ sc, executorKafkaParams, offsetRanges).map { cr =>
+ Row(cr.checksum, cr.key, cr.offset, cr.partition,
cr.serializedKeySize,
+ cr.serializedValueSize, cr.timestamp, cr.timestampType.id,
cr.topic, cr.value)
+ }
+
+ logInfo("GetBatch generating RDD of offset range: " +
+ offsetRanges.sortBy(_.topicPartition.toString).mkString(", "))
+ sqlContext.createDataFrame(rdd, schema)
+ }
+
+ /** Stop this source and free any resources it has allocated. */
+ override def stop(): Unit = synchronized {
+ consumer.close()
+ }
+
+ override def toString(): String = s"KafkaSource[$consumerStrategy]"
+
+ /**
+ * Fetch the offset of a partition, either the latest offsets or the
current offsets in the
+ * KafkaConsumer.
+ */
+ private def fetchPartitionOffsets(
+ seekToLatest: Boolean): Map[TopicPartition, Long] = withRetries {
+
+ // Poll to get the latest assigned partitions
+ logTrace("\tPolling")
+ consumer.poll(0)
+ val partitions = consumer.assignment()
+ consumer.pause(partitions)
+ logDebug(s"\tPartitioned assigned to consumer: $partitions")
+
+ // Get the current or latest offset of each partition
+ if (seekToLatest) {
+ consumer.seekToEnd(partitions)
+ logDebug("\tSeeked to the end")
+ }
+ logTrace("Getting positions")
+ val partitionOffsets = partitions.asScala.map(p => p ->
consumer.position(p)).toMap
+ logDebug(s"Got offsets for partition : $partitionOffsets")
+ partitionOffsets
+ }
+
+ /** Fetch the earliest offsets for newly discovered partitions */
+ private def fetchNewPartitionEarliestOffsets(
+ newPartitions: Seq[TopicPartition]): Map[TopicPartition, Long] =
withRetries {
+
+ // Poll to get the latest assigned partitions
+ logTrace("\tPolling")
+ consumer.poll(0)
+ val partitions = consumer.assignment()
+ logDebug(s"\tPartitioned assigned to consumer: $partitions")
+ require(newPartitions.forall(tp => partitions.contains(tp)),
+ s"$partitions doesn't contain all new paritions: $newPartitions")
+
+ // Get the earliest offset of each partition
+ consumer.seekToBeginning(newPartitions.asJava)
+ val partitionToOffsets = newPartitions.map(p => p ->
consumer.position(p)).toMap
+ logDebug(s"Got offsets for new partitions: $partitionToOffsets")
+ partitionToOffsets
+ }
+
+ /**
+ * Helper function that does multiple retries on the a body of code that
returns offsets.
+ * Retries are needed to handle transient failures. For e.g. race
conditions between getting
+ * assignment and getting position while topics/partitions are deleted
can cause NPEs.
+ */
+ private def withRetries(
+ body: => Map[TopicPartition, Long]): Map[TopicPartition, Long] =
synchronized {
+
+ var result: Option[Map[TopicPartition, Long]] = None
+ var attempt = 1
+ var lastException: Exception = null
+ while (result.isEmpty && attempt <= MAX_OFFSET_FETCH_ATTEMPTS) {
+ try {
+ result = Some(body)
+ } catch {
+ case e: Exception =>
+ lastException = e
+ logWarning(s"Error in attempt $attempt getting Kafka offsets: ",
e)
+ attempt += 1
+ Thread.sleep(OFFSET_FETCH_ATTEMPT_INTERVAL_MS)
+ }
+ }
+ if (result.isEmpty) {
+ assert(attempt > MAX_OFFSET_FETCH_ATTEMPTS)
+ assert(lastException != null)
+ throw lastException
+ }
+ result.get
+ }
+
+ private def positiveMod(a: Long, b: Int): Int = ((a % b).toInt + b) % b
+}
+
+
+/** Companion object for the [[KafkaSource]]. */
+private[kafka010] object KafkaSource {
+
+ val MAX_OFFSET_FETCH_ATTEMPTS = 3
+ val OFFSET_FETCH_ATTEMPT_INTERVAL_MS = 10
+
+ def kafkaSchema: StructType = StructType(Seq(
+ StructField("checksum", LongType),
+ StructField("key", BinaryType),
+ StructField("offset", LongType),
+ StructField("partition", IntegerType),
+ StructField("serializedKeySize", IntegerType),
+ StructField("serializedValueSize", IntegerType),
+ StructField("timestamp", LongType),
+ StructField("timestampType", IntegerType),
+ StructField("topic", StringType),
+ StructField("value", BinaryType)
+ ))
+
+ sealed trait ConsumerStrategy {
+ def createConsumer(): Consumer[Array[Byte], Array[Byte]]
+ }
+
+ case class SubscribeStrategy(topics: Seq[String], kafkaParams:
ju.Map[String, Object])
+ extends ConsumerStrategy {
+ override def createConsumer(): Consumer[Array[Byte], Array[Byte]] = {
+ val consumer = new KafkaConsumer[Array[Byte],
Array[Byte]](kafkaParams)
+ consumer.subscribe(topics.asJava)
+ consumer.poll(0)
+ consumer
+ }
+
+ override def toString: String = s"Subscribe[${topics.mkString(", ")}]"
+ }
+
+ case class SubscribePatternStrategy(
+ topicPattern: String, kafkaParams: ju.Map[String, Object])
+ extends ConsumerStrategy {
+ override def createConsumer(): Consumer[Array[Byte], Array[Byte]] = {
+ val consumer = new KafkaConsumer[Array[Byte],
Array[Byte]](kafkaParams)
+ consumer.subscribe(
+ ju.regex.Pattern.compile(topicPattern),
+ new NoOpConsumerRebalanceListener())
+ consumer.poll(0)
+ consumer
+ }
+
+ override def toString: String = s"SubscribePattern[$topicPattern]"
+ }
+
+ def getSortedExecutorList(sc: SparkContext): Array[String] = {
+ def compare(a: ExecutorCacheTaskLocation, b:
ExecutorCacheTaskLocation): Boolean = {
+ if (a.host == b.host) { a.executorId > b.executorId } else { a.host
> b.host }
+ }
+
+ val bm = sc.env.blockManager
+ bm.master.getPeers(bm.blockManagerId).toArray
+ .map(x => ExecutorCacheTaskLocation(x.host, x.executorId))
+ .sortWith(compare)
+ .map(_.toString)
+ }
+}
+
+
+/** An [[Offset]] for the [[KafkaSource]]. */
+private[kafka010]
+case class KafkaSourceOffset(partitionToOffsets: Map[TopicPartition,
Long]) extends Offset {
--- End diff --
Can we move this into its own file? I would also explain What exactly we
are tracking and why since there has been a lot of confusion on what the
requirements are here.
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